Motion transparency in superimposed dense random-dot patterns: psychophysics and simulation.
To determine the mechanism underlying motion transparency, representative examples of motion transparency are listed and possible mechanisms are suggested. Those are feature tracking, multiple spatial-frequency channels, luminance-based transparency rules, and motion energy. Next, an interesting stimulus for motion transparency is introduced, namely superimposed dense random-dot patterns, which is not explained by feature tracking or multiple spatial-frequency channels. A psychophysical experiment reveals that the occurrence of motion transparency in this stimulus depends on three luminance levels assigned to three possible combinations of component dots: (1) white dots superimposed upon white dots, (2) white dots upon black dots, and (3) black dots upon black dots. However, physical rules of luminance-based transparency fail to explain the results. Finally, a computer simulation reveals that a computational model based on motion energy quantitatively predicts the human psychophysical performance. All the results support the idea that motion-energy detection followed by spatial integration is a likely candidate for the mechanism underlying motion transparency.
Murakami
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Department of Psychology, University of Tokyo, Japan.
D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D009039:Motion Perception; D010364:Pattern Recognition, Visual; D011601:Psychophysics